| /external/tensorflow/tensorflow/contrib/losses/ |
| __init__.py | 16 """Ops for building neural network losses.
18 See @{$python/contrib.losses}.
25 from tensorflow.contrib.losses.python import metric_learning
27 from tensorflow.contrib.losses.python.losses import *
|
| /external/tensorflow/tensorflow/contrib/losses/python/losses/ |
| __init__.py | 15 """Ops for building neural network losses.
17 See @{$python/contrib.losses}.
25 from tensorflow.contrib.losses.python.losses.loss_ops import *
|
| loss_ops.py | 17 Note: All the losses are added to the `GraphKeys.LOSSES` collection.
42 def _scale_losses(losses, weights):
46 losses: A `Tensor` of size [batch_size, d1, ... dN].
48 The `losses` are reduced (tf.reduce_sum) until its dimension matches
49 that of `weights` at which point the reduced `losses` are element-wise
52 `weights` to be the same size as `losses`, performing an element-wise
57 `losses`.
59 # First, compute the sum of the losses over all elements:
61 reduction_indices = list(range(start_index, losses.get_shape().ndims)
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| /external/tensorflow/tensorflow/contrib/keras/api/keras/losses/ |
| __init__.py | 22 from tensorflow.python.keras._impl.keras.losses import binary_crossentropy
23 from tensorflow.python.keras._impl.keras.losses import categorical_crossentropy
24 from tensorflow.python.keras._impl.keras.losses import categorical_hinge
25 from tensorflow.python.keras._impl.keras.losses import cosine_proximity
26 from tensorflow.python.keras._impl.keras.losses import hinge
27 from tensorflow.python.keras._impl.keras.losses import kullback_leibler_divergence
28 from tensorflow.python.keras._impl.keras.losses import logcosh
29 from tensorflow.python.keras._impl.keras.losses import mean_absolute_error
30 from tensorflow.python.keras._impl.keras.losses import mean_absolute_percentage_error
31 from tensorflow.python.keras._impl.keras.losses import mean_squared_erro
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| /external/tensorflow/tensorflow/python/keras/losses/ |
| __init__.py | 22 from tensorflow.python.keras._impl.keras.losses import binary_crossentropy
23 from tensorflow.python.keras._impl.keras.losses import categorical_crossentropy
24 from tensorflow.python.keras._impl.keras.losses import categorical_hinge
25 from tensorflow.python.keras._impl.keras.losses import cosine_proximity
26 from tensorflow.python.keras._impl.keras.losses import hinge
27 from tensorflow.python.keras._impl.keras.losses import kullback_leibler_divergence
28 from tensorflow.python.keras._impl.keras.losses import logcosh
29 from tensorflow.python.keras._impl.keras.losses import mean_absolute_error
30 from tensorflow.python.keras._impl.keras.losses import mean_absolute_percentage_error
31 from tensorflow.python.keras._impl.keras.losses import mean_squared_erro
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| /external/tensorflow/tensorflow/contrib/gan/python/losses/ |
| __init__.py | 15 """TFGAN losses and penalties.
17 Losses can be used with individual arguments or with GANModel tuples.
24 # Collapse losses into a single namespace.
25 from tensorflow.contrib.gan.python.losses.python import losses_wargs as wargs
26 from tensorflow.contrib.gan.python.losses.python import tuple_losses
29 from tensorflow.contrib.gan.python.losses.python.tuple_losses import *
|
| /external/tensorflow/tensorflow/python/ops/losses/ |
| losses.py | 17 Note: All the losses are added to the `GraphKeys.LOSSES` collection by default.
40 from tensorflow.python.ops.losses import util
42 from tensorflow.python.ops.losses.losses_impl import *
43 from tensorflow.python.ops.losses.util import *
|
| util.py | 36 @tf_export("losses.add_loss")
37 def add_loss(loss, loss_collection=ops.GraphKeys.LOSSES):
38 """Adds a externally defined loss to the collection of losses.
48 @tf_export("losses.get_losses")
49 def get_losses(scope=None, loss_collection=ops.GraphKeys.LOSSES):
50 """Gets the list of losses from the loss_collection.
53 scope: An optional scope name for filtering the losses to return.
54 loss_collection: Optional losses collection.
62 @tf_export("losses.get_regularization_losses")
64 """Gets the list of regularization losses
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| losses_impl.py | 29 from tensorflow.python.ops.losses import util
34 @tf_export("losses.Reduction")
39 `NONE`: Un-reduced weighted losses with the same shape as input.
40 `SUM`: Scalar sum of weighted losses.
42 `SUM_OVER_BATCH_SIZE`: Scalar `SUM` divided by number of elements in losses.
100 def _safe_mean(losses, num_present):
101 """Computes a safe mean of the losses.
104 losses: `Tensor` whose elements contain individual loss measurements.
105 num_present: The number of measurable elements in `losses`.
108 A scalar representing the mean of `losses`. If `num_present` is zero
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| /external/tensorflow/tensorflow/python/keras/_impl/keras/ |
| losses_test.py | 34 ALL_LOSSES = [keras.losses.mean_squared_error,
35 keras.losses.mean_absolute_error,
36 keras.losses.mean_absolute_percentage_error,
37 keras.losses.mean_squared_logarithmic_error,
38 keras.losses.squared_hinge,
39 keras.losses.hinge,
40 keras.losses.categorical_crossentropy,
41 keras.losses.binary_crossentropy,
42 keras.losses.kullback_leibler_divergence,
43 keras.losses.poisson
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| metrics.py | 25 from tensorflow.python.keras._impl.keras.losses import binary_crossentropy
26 from tensorflow.python.keras._impl.keras.losses import categorical_crossentropy
27 from tensorflow.python.keras._impl.keras.losses import cosine_proximity
28 from tensorflow.python.keras._impl.keras.losses import hinge
29 from tensorflow.python.keras._impl.keras.losses import kullback_leibler_divergence
30 from tensorflow.python.keras._impl.keras.losses import logcosh
31 from tensorflow.python.keras._impl.keras.losses import mean_absolute_error
32 from tensorflow.python.keras._impl.keras.losses import mean_absolute_percentage_error
33 from tensorflow.python.keras._impl.keras.losses import mean_squared_error
34 from tensorflow.python.keras._impl.keras.losses import mean_squared_logarithmic_erro
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| /external/tensorflow/tensorflow/contrib/gan/python/losses/python/ |
| tuple_losses.py | 21 from tensorflow.contrib.gan.python.losses.python import tuple_losses_impl
22 from tensorflow.contrib.gan.python.losses.python.tuple_losses_impl import *
|
| losses_wargs.py | 21 from tensorflow.contrib.gan.python.losses.python import losses_impl
22 from tensorflow.contrib.gan.python.losses.python.losses_impl import *
|
| losses_impl.py | 15 """Losses that are useful for training GANs.
17 The losses belong to two main groups, but there are others that do not:
28 All losses must be able to accept 1D or 2D Tensors, so as to be compatible with
29 patchGAN style losses (https://arxiv.org/abs/1611.07004).
31 To make these losses usable in the TFGAN framework, please create a tuple
32 version of the losses with `losses_utils.py`.
51 from tensorflow.python.ops.losses import losses
52 from tensorflow.python.ops.losses import util
74 # Wasserstein losses from `Wasserstein GAN` (https://arxiv.org/abs/1701.07875)
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| /external/tensorflow/tensorflow/contrib/losses/python/metric_learning/ |
| __init__.py | 15 """Ops for building neural network losses.
17 See @{$python/contrib.losses}.
25 from tensorflow.contrib.losses.python.metric_learning.metric_loss_ops import *
|
| /external/tensorflow/tensorflow/contrib/kernel_methods/python/ |
| losses_test.py | 15 """Tests for third_party.tensorflow.contrib.kernel_methods.python.losses."""
23 from tensorflow.contrib.kernel_methods.python import losses
39 _ = losses.sparse_multiclass_hinge_loss(labels, logits)
47 _ = losses.sparse_multiclass_hinge_loss(labels, logits)
56 _ = losses.sparse_multiclass_hinge_loss(labels, logits, weights)
64 _ = losses.sparse_multiclass_hinge_loss(labels, logits)
72 _ = losses.sparse_multiclass_hinge_loss(labels, logits, weights=None)
81 _ = losses.sparse_multiclass_hinge_loss(labels, logits, weights)
90 _ = losses.sparse_multiclass_hinge_loss(labels, logits, weights)
98 loss = losses.sparse_multiclass_hinge_loss(labels, logits
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| losses.py | 27 from tensorflow.python.ops.losses import losses
35 loss_collection=ops.GraphKeys.LOSSES,
36 reduction=losses.Reduction.SUM_BY_NONZERO_WEIGHTS):
134 return losses.compute_weighted_loss(
|
| /external/tensorflow/tensorflow/python/kernel_tests/ |
| losses_test.py | 15 """Tests for losses."""
34 from tensorflow.python.ops.losses import losses
35 from tensorflow.python.ops.losses import util
50 losses.absolute_difference(
54 loss = losses.absolute_difference(self._predictions, self._predictions)
59 loss = losses.absolute_difference(self._labels, self._predictions)
65 loss = losses.absolute_difference(self._labels, self._predictions, weights)
71 loss = losses.absolute_difference(self._labels, self._predictions,
78 loss = losses.absolute_difference(self._labels, self._predictions, weights
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| /external/tensorflow/tensorflow/contrib/tpu/python/tpu/ |
| tpu_optimizer.py | 24 from tensorflow.python.ops.losses import losses
34 reduction=losses.Reduction.MEAN,
40 reduction: The reduction to apply to the shard losses.
47 if reduction not in (losses.Reduction.SUM, losses.Reduction.MEAN):
82 if num_shards > 1 and self._reduction == losses.Reduction.MEAN:
|
| /external/tensorflow/tensorflow/contrib/learn/python/learn/ops/ |
| losses_ops.py | 27 from tensorflow.python.ops.losses import losses
30 @deprecated('2016-12-01', 'Use `tf.losses.mean_squared_error` '
39 return predictions, losses.mean_squared_error(labels, predictions)
42 @deprecated('2016-12-01', 'Use `tf.losses.softmax_cross_entropy` '
75 return nn.softmax(logits), losses.softmax_cross_entropy(labels, logits)
|
| /external/tensorflow/tensorflow/python/ops/ |
| nn_xent_test.py | 53 losses = np.array(self._SigmoidCrossEntropyWithLogits(x, y)).reshape(*sizes)
54 return logits, targets, losses
67 logits, targets, losses = self._Inputs(dtype=dtype)
70 np_loss = np.array(losses).astype(np.float32)
78 logits, targets, losses = self._Inputs(dtype=dtype, sizes=[2, 2, 2])
81 np_loss = np.array(losses).astype(np.float32)
129 losses = np.array(self._WeightedCrossEntropy(x, y, q)).reshape(*sizes)
130 return logits, targets, q, losses
142 logits, targets, pos_weight, losses = self._Inputs(dtype=dtypes.float32)
145 np_loss = np.array(losses).astype(np.float32
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| /external/tensorflow/tensorflow/contrib/boosted_trees/python/utils/ |
| losses_test.py | 23 from tensorflow.contrib.boosted_trees.python.utils import losses
51 loss_for_positives, _ = losses.per_example_exp_loss(
54 loss_for_negatives, _ = losses.per_example_exp_loss(
88 loss_tensor, _ = losses.per_example_squared_loss(labels, weights,
|
| /external/tensorflow/tensorflow/contrib/kernel_methods/ |
| __init__.py | 26 from tensorflow.contrib.kernel_methods.python.losses import sparse_multiclass_hinge_loss
|
| /external/tensorflow/tensorflow/contrib/estimator/python/estimator/ |
| multi_head.py | 43 * For training, sums losses of each head, calls `train_op_fn` with this
100 merging losses to calculate the weighted sum of losses from each head. If
101 `None`, all losses are weighted equally.
135 def _merge_losses(losses, head_weights=None):
136 """Merges the given losses into one tensor."""
137 losses = tuple(losses)
139 'merge_losses', values=losses + (head_weights or tuple())):
142 for loss, weight in zip(losses, head_weights)
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| /external/tensorflow/tensorflow/contrib/bayesflow/python/kernel_tests/ |
| layers_dense_variational_test.py | 113 losses = ops.get_collection(ops.GraphKeys.REGULARIZATION_LOSSES)
114 self.assertEqual(len(losses), 0)
115 self.assertListEqual(layer.losses, losses)
120 losses = ops.get_collection(ops.GraphKeys.REGULARIZATION_LOSSES)
121 self.assertEqual(len(losses), 1)
122 self.assertListEqual(layer.losses, losses)
136 losses = ops.get_collection(ops.GraphKeys.REGULARIZATION_LOSSES)
137 self.assertEqual(len(losses), 0
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